Instructions to use frett/chinese_extract_longbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frett/chinese_extract_longbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="frett/chinese_extract_longbert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) model = AutoModelForQuestionAnswering.from_pretrained("frett/chinese_extract_longbert", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 286e823aa15668ab377219225a078e5d0356eba74bfb469f1dfa72229e8d36b7
- Size of remote file:
- 16.4 MB
- SHA256:
- 7a3af8db419b6484eb5a0b8e60a90c4304df284034a4732d294273454c5b5272
路
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